Indoor localization using both radio frequency (RF) and inertial sensors on a mobile device is a common approach. Localization and mapping are performed to compute the most probable location using sensors and control values (if any). Current solutions have considered both the techniques and methods of fusing them. One of the existing solution is inertial navigation using Pedestrian Dead Reckoning (PDR) and particle filter (PF), which is a standard approach. However, it is well-known and evident from experimental results that PDR is susceptible to stride-length inaccuracies and magnetic noise. Another approach is using Received Signal Strength Indication (RSSI) from Radio Frequency (RF) sources on a mobile phone. Since signal strength decays with distance, it is possible to elucidate distance from the same. However, such measurements are corrupted by multipath and fading. Hence, none of the methods are individually correct but can provide location information with some granularity and error distribution.